numpy.expm1() in Python (original) (raw)

Last Updated : 29 Nov, 2018

numpy.expm1(array, out = None, where = True, casting = ‘same_kind’, order = ‘K’, dtype = None) :
This mathematical function helps user to calculate exponential of all the elements subtracting 1 from all the input array elements.

Parameters :

array : [array_like]Input array or object whose elements, we need to test. out : [ndarray, optional]Output array with same dimensions as Input array, placed with result. **kwargs : allows you to pass keyword variable length of argument to a function. It is used when we want to handle named argument in a function. where : [array_like, optional]True value means to calculate the universal functions(ufunc) at that position, False value means to leave the value in the output alone.

Return :

An array with exponential(all elements of input array) - 1.

Code 1 : Working

import numpy as np

in_array = [ 1 , 3 , 5 ]

print ( "Input array : \n" , in_array)

exp_values = np.exp(in_array)

print ( "\nExponential value of array element : "

`` "\n" , exp_values)

expm1_values = np.expm1(in_array)

print ( "\n(Exponential value of array element) - (1) "

`` ": \n" , expm1_values)

Output :

Input array : [1, 3, 5]

Exponential value of array element : [ 2.71828183 20.08553692 148.4131591 ]

(Exponential value of array element) - (1) : [ 1.71828183 19.08553692 147.4131591 ]

Code 2 : Graphical representation

import numpy as np

import matplotlib.pyplot as plt

in_array = [ 1 , 1.2 , 1.4 , 1.6 , 1.8 , 2 ]

out_array = np.expm1(in_array)

print ( "out_array : " , out_array)

y = [ 1 , 1.2 , 1.4 , 1.6 , 1.8 , 2 ]

plt.plot(in_array, y, color = 'blue' , marker = "*" )

plt.plot(out_array, y, color = 'red' , marker = "o" )

plt.title( "numpy.expm1()" )

plt.xlabel( "X" )

plt.ylabel( "Y" )

plt.show()

Output :
out_array : [ 1.71828183 2.32011692 3.05519997 3.95303242 5.04964746 6.3890561 ]

References :
https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.expm1.html#numpy.expm1
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